# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

#' @include arrowExports.R

array_expression <- function(FUN,
                             ...,
                             args = list(...),
                             options = empty_named_list()) {
  structure(
    list(
      fun = FUN,
      args = args,
      options = options
    ),
    class = "array_expression"
  )
}

#' @export
Ops.Array <- function(e1, e2) {
  if (.Generic %in% names(.array_function_map)) {
    expr <- build_array_expression(.Generic, e1, e2)
    eval_array_expression(expr)
  } else {
    stop(paste0("Unsupported operation on `", class(e1)[1L], "` : "), .Generic, call. = FALSE)
  }
}

#' @export
Ops.ChunkedArray <- Ops.Array

#' @export
Ops.array_expression <- function(e1, e2) {
  if (.Generic == "!") {
    build_array_expression(.Generic, e1)
  } else {
    build_array_expression(.Generic, e1, e2)
  }
}

build_array_expression <- function(.Generic, e1, e2, ...) {
  if (.Generic %in% names(.unary_function_map)) {
    expr <- array_expression(.unary_function_map[[.Generic]], e1)
  } else {
    e1 <- .wrap_arrow(e1, .Generic, e2$type)
    e2 <- .wrap_arrow(e2, .Generic, e1$type)
    expr <- array_expression(.binary_function_map[[.Generic]], e1, e2, ...)
  }
  expr
}

.wrap_arrow <- function(arg, fun, type) {
  if (!inherits(arg, c("ArrowObject", "array_expression"))) {
    # TODO: Array$create if lengths are equal?
    # TODO: these kernels should autocast like the dataset ones do (e.g. int vs. float)
    if (fun == "%in%") {
      arg <- Array$create(arg, type = type)
    } else {
      arg <- Scalar$create(arg, type = type)
    }
  }
  arg
}

.unary_function_map <- list(
  "!" = "invert",
  "is.na" = "is_null"
)

.binary_function_map <- list(
  "==" = "equal",
  "!=" = "not_equal",
  ">" = "greater",
  ">=" = "greater_equal",
  "<" = "less",
  "<=" = "less_equal",
  "&" = "and_kleene",
  "|" = "or_kleene",
  "%in%" = "is_in_meta_binary"
)

.array_function_map <- c(.unary_function_map, .binary_function_map)

eval_array_expression <- function(x) {
  x$args <- lapply(x$args, function (a) {
    if (inherits(a, "array_expression")) {
      eval_array_expression(a)
    } else {
      a
    }
  })
  call_function(x$fun, args = x$args, options = x$options %||% empty_named_list())
}

#' @export
is.na.array_expression <- function(x) array_expression("is.na", x)

#' @export
as.vector.array_expression <- function(x, ...) {
  as.vector(eval_array_expression(x))
}

#' @export
print.array_expression <- function(x, ...) {
  cat(.format_array_expression(x), "\n", sep = "")
  invisible(x)
}

.format_array_expression <- function(x) {
  printed_args <- map_chr(x$args, function(arg) {
    if (inherits(arg, "Scalar")) {
      deparse(as.vector(arg))
    } else if (inherits(arg, "ArrowObject")) {
      paste0("<", class(arg)[1], ">")
    } else if (inherits(arg, "array_expression")) {
      .format_array_expression(arg)
    } else {
      # Should not happen
      deparse(arg)
    }
  })
  # Prune this for readability
  function_name <- sub("_kleene", "", x$fun)
  paste0(function_name, "(", paste(printed_args, collapse = ", "), ")")
}

###########

#' Arrow expressions
#'
#' @description
#' `Expression`s are used to define filter logic for passing to a [Dataset]
#' [Scanner].
#'
#' `Expression$scalar(x)` constructs an `Expression` which always evaluates to
#' the provided scalar (length-1) R value.
#'
#' `Expression$field_ref(name)` is used to construct an `Expression` which
#' evaluates to the named column in the `Dataset` against which it is evaluated.
#'
#' `Expression$compare(OP, e1, e2)` takes two `Expression` operands, constructing
#' an `Expression` which will evaluate these operands then compare them with the
#' relation specified by OP (e.g. "==", "!=", ">", etc.) For example, to filter
#' down to rows where the column named "alpha" is less than 5:
#' `Expression$compare("<", Expression$field_ref("alpha"), Expression$scalar(5))`
#'
#' `Expression$and(e1, e2)`, `Expression$or(e1, e2)`, and `Expression$not(e1)`
#' construct an `Expression` combining their arguments with Boolean operators.
#'
#' `Expression$is_valid(x)` is essentially (an inversion of) `is.na()` for `Expression`s.
#'
#' `Expression$in_(x, set)` evaluates x and returns whether or not it is a member of the set.
#' @name Expression
#' @rdname Expression
#' @export
Expression <- R6Class("Expression", inherit = ArrowObject,
  public = list(
    ToString = function() dataset___expr__ToString(self)
  )
)

Expression$field_ref <- function(name) {
  assert_is(name, "character")
  assert_that(length(name) == 1)
  dataset___expr__field_ref(name)
}
Expression$scalar <- function(x) {
  dataset___expr__scalar(Scalar$create(x))
}
Expression$compare <- function(OP, e1, e2) {
  comp_func <- comparison_function_map[[OP]]
  if (is.null(comp_func)) {
    stop(OP, " is not a supported comparison function", call. = FALSE)
  }
  comp_func(e1, e2)
}

comparison_function_map <- list(
  "==" = dataset___expr__equal,
  "!=" = dataset___expr__not_equal,
  ">" = dataset___expr__greater,
  ">=" = dataset___expr__greater_equal,
  "<" = dataset___expr__less,
  "<=" = dataset___expr__less_equal
)
Expression$in_ <- function(x, set) {
  dataset___expr__in(x, Array$create(set))
}
Expression$and <- function(e1, e2) {
  dataset___expr__and(e1, e2)
}
Expression$or <- function(e1, e2) {
  dataset___expr__or(e1, e2)
}
Expression$not <- function(e1) {
  dataset___expr__not(e1)
}
Expression$is_valid <- function(e1) {
  dataset___expr__is_valid(e1)
}

#' @export
Ops.Expression <- function(e1, e2) {
  if (.Generic == "!") {
    return(Expression$not(e1))
  }
  make_expression(.Generic, e1, e2)
}

make_expression <- function(operator, e1, e2) {
  if (operator == "%in%") {
    # In doesn't take Scalar, it takes Array
    return(Expression$in_(e1, e2))
  }

  # Handle unary functions before touching e2
  if (operator == "is.na") {
    return(is.na(e1))
  }
  if (operator == "!") {
    return(Expression$not(e1))
  }

  # Check for non-expressions and convert to Expressions
  if (!inherits(e1, "Expression")) {
    e1 <- Expression$scalar(e1)
  }
  if (!inherits(e2, "Expression")) {
    e2 <- Expression$scalar(e2)
  }
  if (operator == "&") {
    Expression$and(e1, e2)
  } else if (operator == "|") {
    Expression$or(e1, e2)
  } else {
    Expression$compare(operator, e1, e2)
  }
}

#' @export
is.na.Expression <- function(x) !Expression$is_valid(x)
